Masoud Mohammadi

A graphSAGE discovers synergistic combinations of Gefitinib, paclitaxel, and Icotinib for Lung adenocarcinoma management by targeting human genes and proteins: the RAIN protocol

The paper proposes a method using graph neural networks to recommend drug combinations for lung adenocarcinoma by targeting genes and proteins, finding Gefitinib, Paclitaxel, and Icotinib as the most effective combination.

Systematic review and network meta-analysis of drug combinations suggested by machine learning on genes and proteins, with the aim of improving the effectiveness of Ipilimumab in treating Melanoma.

This paper proposes a drug combination for Melanoma treatment using machine learning on genes and proteins, showing a 74-fold increase in effectiveness compared to single drugs.

Drug combinations proposed by machine learning on genes/proteins to improve the efficacy of Tecovirimat in the treatment of Monkeypox: A Systematic Review and Network Meta-analysis.

This study uses machine learning to identify drug combinations that improve Tecovirimat efficacy for Monkeypox, showing significant reductions in p-values for treatment scenarios.

Recommending Drug Combinations using Reinforcement Learning to target Genes/proteins that cause Stroke: A comprehensive Systematic Review and Network Meta-analysis

This paper uses reinforcement learning to recommend drug combinations targeting genes/proteins involved in stroke, showing improved efficacy and reduced p-values in network meta-analysis.